a Grid Computing System - Utopia

Graphical representation of results:
6. Performance Testing
Analysis of results: What we observed confirms our intuition that when the task size increase
(so the task number decrease), the overhead will decrease. So, by having less tasks, the
network/JavaSpace overhead decrease, so does the exectuion time, to a certain point. After
that point, the execution time begins to increase slightly again.
This is caused by two factors. One is that the number of tasks is not always a multiple of
the number of producers, so there are times (to the end of the application runtime) that some
producers are idle during the life time of the application. The other factor is that not all the
task are of equal size in terms of computational time. Even if the cunks are equal, some tasks
will require more computation than others. If the tasks more computation-intensive will be
taken last (we are using eager scheduling), than again there will be some producers that will
remai idle. This explains the anomaly of increase in execution time to the end of the scale of
tasks number.
6.2.2. Varying the Number of Producers
Objectives: To explore the possible speedup that can be obtained by increasing more producers
and to understand the factors that might limit the speedup.
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